543 A machine-learning CMR approach to extract disease features and automate pulmonary arterial hypertension diagnosis

Swift, A.J., Lu, H. orcid.org/0000-0002-0349-2181, Garg, P. orcid.org/0000-0002-5483-169X et al. (8 more authors) (2019) 543 A machine-learning CMR approach to extract disease features and automate pulmonary arterial hypertension diagnosis. In: European Heart Journal - Cardiovascular Imaging. EuroCMR 2019, 02-04 May 2019, Venice, Italy. Oxford University Press (OUP) .

Metadata

Authors/Creators:

Swift, A.J.
Lu, H. https://orcid.org/0000-0002-0349-2181
Garg, P. https://orcid.org/0000-0002-5483-169X
Taylor, J.
Metherall, P.
Zhou, S.
Johns, C.
Condliffe, R.A.
Lawrie, A. https://orcid.org/0000-0003-4192-9505
Wild, J.M. https://orcid.org/0000-0002-7246-8660
Kiely, D.G. https://orcid.org/0000-0003-0184-6502

Copyright, Publisher and Additional Information:

© 2019 The Author(s).

Keywords:

diagnosis; pulmonary arterial hypertension; cardiac mri; machine learning

Dates:

Published (online): 4 June 2019
Published: June 2019

Institution:

The University of Sheffield

Academic Units:

The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
The University of Sheffield > Sheffield Teaching Hospitals

Funding Information:

Funder	Grant number
British Heart Foundation	FS/13/48/30453

Depositing User:

Symplectic Sheffield

Date Deposited:

16 Jul 2019 09:40

Last Modified:

16 Jul 2019 09:40

Status:

Published

Publisher:

Oxford University Press (OUP)

Refereed:

Yes

Identification Number:

https://doi.org/10.1093/ehjci/jez104.001

Related URLs:

Conference

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